Credit David Cearley
Trend No. 1: Autonomous things
Whether it’s cars, robots or agriculture, autonomous things use AI to perform tasks traditionally done by humans. The sophistication of the intelligence varies, but all autonomous things use AI to interact more naturally with their environments.
Autonomous things exist across five types:
Trend No. 2: Augmented analytics
Augmented analytics represents a third major wave for data and analytics capabilities as data scientists use automated algorithms to explore more hypotheses. Data science and machine learning platforms have transformed how businesses generate analytics insight.
“By 2020, more than 40% of data science tasks will be automated”
Augmented analytics identify hidden patterns while removing the personal bias. Although businesses run the risk of unintentionally inserting bias into the algorithms, augmented analytics and automated insights will eventually be embedded into enterprise applications.
Trend No. 3: AI-driven development
This trend is evolving along three dimensions:
1. The tools used to build AI-powered solutions are expanding from tools targeting data scientists (AI infrastructure, AI frameworks and AI platforms) to tools targeting the professional developer community (AI platforms, AI services).
2. The tools used to build AI-powered solutions are being empowered with AI-driven capabilities that assist professional developers and automate tasks related to the development of AI-enhanced solutions.
3. AI-enabled tools are evolving from assisting and automating functions related to application development (AD) to being enhanced with business domain expertise and automating activities higher on the AD process stack (from general development to business solution design).
Trend No. 4: Digital twins
A digital twin is a digital representation that mirrors a real-life object, process or system. The idea of a digital twin is not new. It goes back to computer-aided design representations of things or online profiles of customers, but today’s digital twins are different in four ways:
The robustness of the models, with a focus on how they support specific business outcomes
The link to the real world, potentially in real time for monitoring and control
The application of advanced big data analytics and AI to drive new business opportunities
The ability to interact with them and evaluate “what if” scenarios
Trend No. 5: Empowered edge
Edge computing is a topology where information processing and content collection and delivery are placed closer to the sources of the information, with the idea that keeping traffic local will reduce latency. Currently, much of the focus of this technology is a result of the need for IoT systems to deliver disconnected or distributed capabilities into the embedded IoT world. This type of topology will address challenges ranging from high WAN costs and unacceptable levels of latency. Further, it will enable the specifics of digital business and IT solutions.
“Technology and thinking will shift to a point where the experience will connect people with hund